Case Study | Meet Daniel

Brand Reputation Manager


Problem:

Daniel is in charge of brand and reputation management for a nationwide healthcare service. Typically, Daniel’s day is spent inside the world of social networks, filtering through endless posts and monitoring customer discontent with a goal to reduce additional negative posts and to improve brand perception.   He needs more people and more time to get to all the posts but that is too expensive. Daniel feels he is more reactive than proactive and needs to find a new preventive solution to do his job more efficiently, and get to more of the feedback.

Solution:

When customer online trends started to focus negatively about the quality of the doctors, Daniel and team employed speech analytics to evaluate the types of chat conversations coming into customer service. Daniel also wanted to evaluate all the emails being received and compare them to the social feedback received. Running all the social feedback thought the same analytics engine afforded Daniel a total view of what might be causing the bad reviews. While online reports insinuated the doctor’s office was unethical, they found through LucidvueCX analytics that actually the root cause was a discrepancy with a corporate payment policy. Daniel quickly made a change to the policy and how it was communicated to reduce the customer frustration.

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